Publications

2013

  • "Binary particle swarm optimisation with improved scaling behaviour", D Gorse, in: in: M Verleysen (ed), Proceedings of ESANN 2013, 239-244, 2013.
  • "A novel application of particle swarm optimisation to optimal trade execution", M Saeidi and D Gorse, in: M Lee et al (eds), ICONIP 2013, Part II, LNCS 8227, 448-455, 2013.
  • "Identification of the predictability of steel manufacturer stock price movements using particle swarm optimisation", P Khoury and D Gorse, in: M Lee et al (eds), ICONIP 2013, Part II, LNCS 8227, 673-680, 2013.
2012
  • "Identification of factors characterising volatility and firm-specific risk using ensemble classifiers", P Khoury and D Gorse, in: T Huang et al (eds), ICONIP 2012, Part IV, LNCS 7666, 450-457, 2012.
  • "Extracting key gene regulatory dynamics for the direct control of mechanical systems", J Krohn and D Gorse, in: C A Coello et al (eds), PPSN 2012, Part I, LNCS 7491, 468-477, 2012.
  • "Construction of emerging markets exchange traded funds using multiobjective particle swarm optimisation", M Diez-Fernandez, S Alvarez Telena and D Gorse, in: A E P Villa et al (eds), ESANN 2012, Part II, LNCS 7553, 140-147, 2012.
2011
  • "Application of stochastic recurrent reinforcement learning to index trading", D Gorse, in: M Verleysen (ed), Proceedings of ESANN 2011, 123-128, 2011.
2010
  • "Fractal gene regulatory networks for control of nonlinear systems", J Krohn and D Gorse, in: R Schaefer et al (eds), PPSN 2010, Part II, LNCS 6239, 209-218, 2010.
2005
  • "Morphological aspects of oligomeric protein structures", H Postingl, T Kabir, D Gorse, H Postingl and J M Thornton, Progress in Biophysics and Molecular Biology, 89(1), 9-35, 2005.
2003
  • "A novel approach to the recognition of protein architecture from sequence using Fourier analysis and neural networks", A J Shepherd, D Gorse and J M Thornton, Proteins, 50(2), 290-302, 2003.
2002

  • "Wavelet transforms for the characterization and detection of repeating motifs", K Murray, D Gorse and J M Thornton, Journal of Molecular Biology, 316(2), 341-363, 2002.

  • "Application of a chaperone-based refolding method to 2- and 3-dimensional off-lattice protein models", D Gorse, Biopolymers, 64(3), 146-160, 2002.

2001

  • "Global minimisation of an off-lattice potential energy function using a chaperone-based refolding method", D Gorse, Biopolymers, 59(6), 411-426, 2001.

  • "Speaker identification for security systems using reinforcement-trained pRAM neural network architectures", T G Clarkson, C C Christodoulou, Y Guan, D Gorse, D A Romano-Critchley and J G Taylor, IEEE Trans. Syst. Man Cyb., 31(1), 65-76, 2001.
1999

  • "Prediction of the location and type of beta-turns in proteins using neural networks", A J Shepherd, D Gorse and J M Thornton, Protein Science, 8(5), 1045-1055, 1999.

1997

  • "Application of weak classifier architectures to protein structure classification", D Gorse, in: Proceedings of ECSAP-97, Prague, June 1997, pp 383-386.

  • "The new ERA in supervised learning", D Gorse, A Shepherd and J G Taylor, Neural Networks, 10, 343-352, 1997.

  • "A pulse-based reinforcement algorithm for learning continuous functions", D Gorse, D A Romano-Critchley and J G Taylor, Neurocomputing, 14, 319-344, 1997.
1996
  • "A modular pRAM architecture for the classification of TESPAR-encoded speech signals", D Gorse and D A Romano-Critchley, Neural Network World, 6, 299-304, 1996.
  • "Binary state machines for arithmetic operations on pulse-coded signals", D Gorse, in: Proceedings of ICONIP'96, Hong Kong, September 1996, pp 563-566.
1995
  • "Learning real-valued univariate time series: an application of a pulse-based reinforcement algorithm for learning continuous functions using pRAMs", D Gorse and D A Romano-Critchley, in: Proceedings of the Weightless Neural Network Workshop '95 (WNNW'95), ed. David Bisset, pp 35-39.
  • "An architecture for the learning of real-to-binary mappings using binary-output reinforcement training", D Gorse and D A Romano-Critchley, in: Proceedings of the Weightless Neural Network Workshop '95 (WNNW'95), ed. David Bisset, pp 70-75.
  • "Application of a pulse-based reinforcement algorithm for learning continuous functions using pRAMs: the sunspot prediction problem", D Gorse and D A Romano-Critchley, in: Proceedings of ICANN '95, Paris, October 1995, pp 227-232.
1994
  • "A classical algorithm for avoiding local minima", D Gorse, A Shepherd and J G Taylor, in: Proceedings of WCNN '94, San Diego, June 1994, pp III-364 - III-369.
  • "Avoiding local minima by a classical range expansion algorithm", D Gorse, A Shepherd and J G Taylor, in: Proceedings of ICANN '94, Sorrento, May 1994, Vol 1, pp 525-528.

  • "Noisy reinforcement training for pRAM nets", Y Guan, T Clarkson, J Taylor and D Gorse, Neural Networks, 7, 523-538, 1994.
  • "Temporal difference learning using a pulse-based reinforcement training algorithm", D Gorse, J G Taylor and T G Clarkson, in: Proceedings of ICONIP '94, Seoul, October 1994, pp 293-298.
  • "A pulse-based reinforcement algorithm for learning continuous functions", D Gorse, J G Taylor and T G Clarkson, in: Proceedings of WCNN '94, San Diego, June 1994, pp II-73 - II-78.
  • "Extended functionality for probabilistic RAM neurons", D Gorse, J G Taylor and T G Clarkson, in: Proceedings of ICANN '94, Sorrento, May 1994, Vol 1, pp 705-708.
1993
  • "Tracking global minima by progressive range expansion", D Gorse, A Shepherd and J G Taylor, in: Proceedings of IJCNN '93, Portland, Oregon, July 1993, pp IV-350 - IV-353.
  • "Avoiding local minima using a range expansion algorithm", D Gorse, A Shepherd and J G Taylor, Neural Network World, 5, 503-510 (1993).

  • "Generalization in probabilistic RAM nets", T G Clarkson, Y Guan, J G Taylor and D Gorse, IEEE Transactions on Neural Networks, 4, 360-363, 1993.
  • "A hardware-implementable algorithm for learning non-linear functions", D Gorse, J G Taylor and T G Clarkson, in: Proceedings of IJCNN '93, Nagoya, October 1993, pp I-911 - I-914.
  • "Learning real-valued functions using a stochastic reinforcement algorithm", D Gorse, J G Taylor and T G Clarkson, in: Proceedings of IJCNN '93, Portland, Oregon, July 1993, pp III-301 - III-304.
  • "A Stochastic Reverse Interpolation Algorithm for Real-Valued Function Learning", Y Guan, T G Clarkson, J G Taylor and D Gorse, in: Proceedings of the 3rd IEE Int. Conf. on Artificial Neural Networks, Brighton, May 1993.
  • "A review of the theory of pRAMs", D Gorse and J G Taylor, in: Proceedings of the Weightless Neural Network Workshop '93, York, April 1993, pp 13-17.
1992
  • "Adding stochastic search to conjugate gradient algorithms", D Gorse and A Shepherd, Neural Network World, 2, 599-605, 1992.
  • "Classical and stochastic search in conjugate gradient algorithms", D Gorse, in: Proceedings of IJCNN '92, Beijing, November 1992, pp 435-440.

  • "Learning probabilistic RAM nets using VLSI structures" , T G Clarkson, C K Ng, D Gorse and J G Taylor, IEEE Transactions on Computers, 41, 1552-1561, 1992.
  • "From wetware to hardware: reverse engineering using probabilistic RAMs", T G Clarkson, D Gorse and J G Taylor, Journal of Intelligent Systems, 2, 11-30, 1992.
  • "A noisy training method for digit recognition using pRAM neural networks", Y Guan, T G Clarkson, J G Taylor and D Gorse, in: Proceedings of IJCNN '92, Beijing, November 1992, pp 673-678.
  • "The use of encoded outputs and reinforcement training", Y Guan, T Clarkson, J G Taylor and D Gorse, in: Proceedings of ICANN '92, Brighton, September 1992, pp 653-656.
  • "The noisy-leaky integrator model implemented using pRAMs", J G Taylor, T G Clarkson, C Christodoulou and D Gorse, in: Proceedings of IJCNN '92, Baltimore, June 1992, pp 178-183.
  • "The application of noisy reward/penalty learning to pyramidal pRAM structures", Y Guan, T G Clarkson, D Gorse and J G Taylor, in: Proceedings of IJCNN '92, Baltimore, June 1992, pp 660-665.
  • "Associative reinforcement training using probabilistic RAM nets", D Gorse, in: Neural Network Dynamics, eds. J G Taylor, E R Caianello, R M J Cotterill and J W Clark, Springer, Berlin, 1992, pp 19-29.
1991
  • "A continuous input RAM-based stochastic neural model", D Gorse and J G Taylor, Neural Networks, 4, 657-665, 1991.
  • "Universal associative stochastic learning automata", D Gorse and J G Taylor, Neural Network World, 1, 193-202, 1991.
  • "Training strategies for probabilistic RAMs",D Gorse and J G Taylor, in: Theory and Applications of Neural Networks, eds J G Taylor and C L T Mannion, Springer, 1991, pp 211-217.
  • "Encoding temporal structure in probabilistic RAM nets", D Gorse and J G Taylor, in: Proceedings of the Second IEE International Conference on Artificial Neural Networks, Bournemouth, November 1991, pp 369-372.
  • "Applications of the pRAM", T G Clarkson, D Gorse, Y Guan and J G Taylor, in: Proceedings of IJCNN '91, Singapore, September 1991, pp 2618-2623.
  • "Learning sequential structure with recurrent pRAM nets", D Gorse and J G Taylor, in: Proceedings of IJCNN '91, Seattle, July 1991, pp 37-42.
  • "A serial-update VLSI architecture for the learning probabilistic neuron", T G Clarkson, C K Ng, D Gorse and J G Taylor, in: Proceedings of ICANN '91, Helsinki, June 1991, pp 1573-1576.
  • "Biologically plausible learning in hardware realisable nets", T G Clarkson, D Gorse and J G Taylor, in: Proceedings of ICANN '91, Helsinki, June 1991, pp 195-199.
1990
  • "A general model of stochastic neural processing", D Gorse and J G Taylor, Biol. Cybern., 63, 299-306, 1990.
  • "Reinforcement training strategies for probabilistic RAMs", D Gorse and J G Taylor, in: Theoretical Aspects of Neurocomputing, eds. M Novak and E Pelikan, World Scientific (1990), pp 180-184.
  • "Training strategies for probabilistic RAMs",D Gorse and J G Taylor, in: Parallel Processing in Neural Systems and Computers, eds R Eckmiller, G Hartmann and G Hauske, North-Holland, 1990, pp 161-164.
  • "pRAM automata", T G Clarkson, D Gorse and J G Taylor, in: Proceedings of 1990 IEEE International Workshop on Cellular Neural Networks and their Applications, Budapest, December 1990, pp 235-243.
  • "Hardware realisable learning algorithms", D Gorse and J G Taylor, in: Proceedings of the International Neural Network Conference, Paris, July 1990, pp 821-824.
1989
  • "An analysis of noisy RAM and neural nets",D Gorse and J G Taylor, Physica D, 34, 90-114, 1989.
  • "A new model of the neuron", D Gorse, in: New Developments in Neural Computing, eds. J G Taylor and C L T Mannion, Adam Hilger (1989), pp 111-118.
  • "Towards a hardware realisable model of the neuron", D Gorse and J G Taylor, in: Models of Brain Function, ed. Rodney M J Cotterill, CUP (1989).
  • "Hardware realisable models of neural processing", T G Clarkson, D Gorse and J G Taylor, in: Proceedings of the First IEE International Conference on Artificial Neural Networks, 1989, pp 242-246.
1988
  • "On the equivalence and properties of noisy neural and probabilistic RAM nets", D Gorse and J G Taylor, Physics Letters A, 131, 326-332, 1988.